The classification models (logistic regression and random forest) had statistical recall and precision similar to or greater than those of the time-to-event models (Cox proportional hazards regression and random survival forest). However, the time-to-event models provided predictions that could potentially better indicate to clinicians whether and when a patient is likely to experience cardiopulmonary arrest.

Conclusions

As early warning scoring systems are refined, they must use the best analytical methods that both model the underlying phenomenon and provide an understandable prediction.